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AJNR Am J Neuroradiol. 2000 Mar;21(3):561-7.

Multivariate feature analysis of sonographic findings of metastatic cervical lymph nodes: contribution of blood flow features revealed by power Doppler sonography for predicting metastasis.

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  • 1Department of Radiology and Cancer Biology, Nagasaki University School of Dentistry, Japan.



Sonographic criteria of the lymph node have been found to be good indicators for metastatic lymph nodes. We determined which sonographic features are most predictive of metastasis in cervical lymph nodes among patients with head and neck cancer.


Gray-scale and power Doppler sonograms were retrospectively analyzed in 133 cervical lymph nodes (57 metastatic and 76 reactive nodes) from 52 patients with head and neck cancer. The gray-scale sonographic features of the presence or absence of hilar echoes, parenchymal echogenicity, and short and long axis lengths as well as the power Doppler features of normal hilar flow and abnormal parenchymal flow were evaluated. Univariate and multivariate logistic regression analyses were conducted to determine the relative value of each sonographic feature.


At univariate analysis, all sonographic features assessed were found to be important. Multivariate analysis, however, suggested that the presence or absence of hilar echoes, increases in short axis length, and the presence of normal hilar flow were the only sonographic features that were predictive of reactive (presence of hilar echoes and hilar flow) and metastatic (increases in short axis length) lymph nodes. Although multivariate analysis did not indicate any significant contribution of the color-flow criteria for predicting metastatic nodes, the color-flow criteria appeared to improve the overall diagnostic accuracy for the less experienced observer.


The sonographic criteria most predictive of metastatic cervical lymph nodes were absent hilar echoes and increases in short axis length, as assessed by logistic regression analysis. Compared with these gray-scale criteria, color-flow criteria had fewer predictive advantages.

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